pythonpandasdataframepandas-explode

Pandas Explode on Multiple columns

Using Pandas 0.25.3, trying to explode a couple of columns.

Data looks like:

d1 = {'user':['user1','user2','user3','user4'],
      'paid':['Y','Y','N','N']
      'last_active':['11 Jul 2019','23 Sep 2018','08 Dec 2019','03 Mar 2018'],
      'col4':'data'}

I sent this to a dataframe df=pd.DataFrame([d1],columns=d1.keys()) that looks like this:

user                              paid              last_active                                                col4               
['user1','user2','user3','user4'] ['Y','Y','N','N'] ['11 Jul 2019','23 Sep 2018','08 Dec 2019','03 Mar 2018']  'data'

there are other columns as well with one value per, {'A':'B'} type stuff, but I'm not worried about those.

when I do df.explode('user') it works for that one, and same for the other columns, but when I try to do df.explode(column=('user','paid','last_active') it gives me the following error:

KeyError: ('user','paid','last_active')

So what I want to know, is how can I explode it with the explode function on multiple columns to get the following df:

user     paid  last_active    col4
'user1'  'Y'   '11 Jul 2019'  'data'
'user2'  'Y'   '23 Sep 2018'  NaN
'user3'  'N'   '08 Dec 2019'  NaN
'user4'  'N'   '03 Mar 2018'  NaN
Solution

  • I guess you need (note the difference in data for col4 which has None as OP mentioned):

    pd.DataFrame([[i] if not isinstance(i,list) else i 
             for i in d1.values()],index=d1.keys()).T

        user paid  last_active  col4
0  user1    Y  11 Jul 2019  data
1  user2    Y  23 Sep 2018  None
2  user3    N  08 Dec 2019  None
3  user4    N  03 Mar 2018  None